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OpenEvidence is a medical AI platform used by over 40% of US clinicians. The company is a $12B organization with a 30-person engineering team composed of talent from MIT, Harvard, and Stanford. They are seeking exceptional engineers and scientists to join their team and help define the default platform for medical AI.
The role is a Member of Technical Staff focused on beneficial deployments. This is an individual contributor position for a world-class engineer or scientist who wants to work on bleeding-edge medical AI technology with direct impact on hundreds of millions of lives.
OpenEvidence's culture emphasizes end-to-end ownership, uncompromising excellence, and autonomous builders. Engineers are responsible for landing major product improvements without separate product managers. The company values precision, intentionality, developer velocity, and shipping impact. Work is expected to be hard, detailed-oriented, and focused on completing and announcing important projects.
The ideal candidate is a brilliant builder who is smart, ambitious, scrappy, autonomous, precise, motivated, hard-working, and low-ego. The company is looking for people who want to lean in and get hands-on building something from nothing, not those looking to complete assigned tickets or write papers.
The company values specific technical spikes in several areas: fullstack development with end-to-end ownership; frontend/mobile with extreme attention to detail and beautiful UI; machine learning with research background but preference for building over papers; infrastructure/site reliability for mission-critical systems; speed optimization; and applied AI systems that thoughtfully leverage modern models.
The engineering team works in-person 5 days per week in SF and Miami offices. The company provides meals, transport, and other support to optimize for focus and productivity.
Requirements: The posting does not specify explicit years of experience or formal education requirements. However, the ideal candidate demonstrates: world-class engineering or scientific capability; experience building end-to-end products; ability to take autonomous ownership of major projects; attention to detail and precision; experience shipping products at scale; and ideally expertise in one or more of the following areas: fullstack development, frontend/mobile, machine learning, infrastructure/SRE, performance optimization, or applied AI systems.
